{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "data = pd.read_json('trump_tweets_2009~2018.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qzaNz1/DDpmwGt2/mdCSpQCquIiIiIiJyTHkFxby7eBtvLdhK9qEiejYP4cWrO9OzhXee\ngntt9ya8u3gb//hiHf3bhFPDT7f0qSpO+p00xjQ2xnxvjFlnjFljjLnLM/43Y0yGMWaF5+3iMvs8\naIxJNcZsMMZcVGZ8iGcs1RjzwNn5lERERERE5Ezk5Bfxwtcb6f30d/xr/gbiouvy8a09mTG+B71a\nhnplaQXw8/Xh4UvakbYvn3cXpzkdRypQeWZcS4B7rLXJxpggIMkY87XnuRestc+W3dgYEwtcA7QH\nIoFvjDGtPU+/AgwC0oHlxphPrLVrK+ITERERERGRM+NyWyb/kMrkHzZzqMjF4NiGTLygJXHR9ZyO\nVm7924Rzfusw/v3tJkbER9MgsIbTkaQCnHTG1Vqbaa1N9nycB6wDok6wy+XAh9baQmvtViAV6O55\nS7XWbrHWFgEferYVERERERGH5eQXcePU5Tz71Ub6tApl3p/6MuWGhEpVWo94+JJ25Be5ePGbjSff\nWCqFUzrp2xgTA3QBlnqGJhpjVhlj3jbG1PeMRQE7yuyW7hk73vhvjzHeGJNojEnUXcBERERERM6+\nlIxchr28gEWb9/Lk8A68dn1X2kYEOx3rtLVqGMS13Zvw/tLtbNqV53QcqQDlLq7GmDrALOBP1toD\nwGSgBdAZyASeO7LpMXa3Jxj/9YC1U6y1CdbahLCwsPLGExERERGR0zArKZ2RkxdRXGKZeUtPrjuv\nqddew3oq7h7Umto1fHni83VOR5EKUK7iaozxp7S0vm+tnQ1grd1lrXVZa93AG5SeCgylM6mNy+we\nDew8wbiIiIiIiJxjRSVuHpmTwj3/WUmXJvX47M4+dGlS/+Q7VhINAmtw5wWt+HHjHn7YsNvpOHKG\nynNXYQO8Bayz1j5fZrxRmc2GAymejz8BrjHG1DTGNANaAcuA5UArY0wzY0wNSm/g9EnFfBoiIiIi\nIlJeWbkFXD1lMe8t2cb4fs2Z/sfzCK1T0+lYFW5MrxhiQmrz5OfrKHG5nY4jZ6A8dxXuDYwGVhtj\nVnjGHgJGGWM6U3q6bxpwC4C1do0xZiawltI7Ek+w1roAjDETgfmAL/C2tXZNBX4uIiIiIiJyEku2\n7GPiB8nkF7l45dp4LolrdPKdKqkafj48eHE7bnkviRnLtjO6Z4zTkeQ0GWt/d5mp10hISLCJiYlO\nxxARERERqfSstby1YCtPfbmepiG1ef36rrRqGOR0rLPOWsuoN5awISuPH+4dQN1a/k5HkjKMMUnW\n2oSTbXdKdxUWEREREZHK51BhCXfM+IUnPl/HwHbhzJ3Qu1qUVgBjDI9cGkvO4WJe+naT03HkNKm4\nioiIiIhUYVv2HGT4qwv5YnUm9w9py2vXdyUooHrNOraPrMuVXaOZtjiNrXsPOR1HToOKq4iIiIhI\nFfXVmiwuf3khe/IKeffG87itf4sqsdTN6fjL4Db4+/rw1BdaHqcyUnEVEREREaliXG7Lv+avZ/x7\nSTQLC+SzO/vSp1Wo07EcFR4cwIQBLflq7S4Wbd7rdBw5RSquIiIiIiJVSPahIsa+s4xXvt/MNd0a\nM/OWnkTVq+V0LK/wxz7NiKpXiyc+W4fL7b03qZXfU3EVEREREakiVqfnMuylBSzdks1TIzry9Mg4\nAvx9nY7lNQL8fbl/aFvWZh5gVlK603HkFKi4ioiIiIhUATOX72Dka4uw1vKfW3syqnsTpyN5pWFx\njYhvUo9n5m/gYGGJ03GknFRcRUREREQqscISFw/OXs19s1bRLaY+n97Rh06N6zkdy2sdWR5n78FC\nJv+Q6nQcKScVVxERERGRSmpnzmGuen0JM5Zt59bzWzBtXHdC6tR0OpbX69KkPld0juSNn7eSvj/f\n6ThSDiquIiIiIiKV0KLUvQx7aQGpu/J47fp4HhjaFj9f/XpfXvcNaYuPgX/O2+B0FCkH/ZctIiIi\nIlKJWGt5/cfNXP/WUurV9mfuxD4M6dDI6ViVTmS9Wozv25xPV+4kaVu203HkJFRcRUREREQqiYOF\nJUz4IJmnvlzPRe0jmDuxDy3D6zgdq9K65fwWhAfV5P8+W4dby+N4NRVXEREREZFKIHX3Qa54ZSHz\nUrJ46OK2vHpdPHVq+jkdq1ILrOnHvRe1YeWOHD5ZudPpOHICKq4iIiIiIl5uXkomV7yykP2Hiph+\n03mM79cCY4zTsaqEkfHRdIgK5p/z1nO4yOV0HDkOFVcRERERES9V4nLz9JfruXV6Mi3C6/DpHX3o\n1SLU6VhVio+P4ZFLYsnMLeCNn7c4HUeOQ8VVRERERMQL7TtYyA1vL+O1Hzdz7XlNmHlLDyLr1XI6\nVpV0XvMQhnaIYPIPm9l1oMDpOHIMKq4iIiIiIl5m5Y4chr20gMRt+3nmD3H8Y3hHavr5Oh2rSntw\naDtcbsszWh7HK6m4ioiIiIh4kRnLtnPla4sxxjDr1l5cldDY6UjVQpOQ2ozrHcOs5HRWp+c6HUd+\nQ8VVRERERMQLFBS7uP/jVTw4ezXnNW/Ap3f0oWN0XadjVSsTLmhJSGANHv9sLdZqeRxvouIqIiIi\nIuKw9P35XPX6Yj5K3MGEAS2YOq47DQJrOB2r2gkO8OfuQa1ZlpbNvJQsp+NIGSquIiIiIiIOWrBp\nL8NeWsDWPYeYMror917UFl8fLXXjlGu6NaZNwyCe+nI9hSVaHsdbqLiKiIiIiDjAWsurP6Ryw9tL\nCa1Tk7kTezO4fYTTsao9P18fHr60Hduz85m6MM3pOOKh4ioiIiIico7lFRRz6/Qknpm3gaEdGzFn\nQm+ah9VxOpZ49G0VxgVtw3npu1T2Hix0Oo6g4ioiIiIick4VFLsY+85yvlm3m4cvacfLo7oQWNPP\n6VjyGw9d3I6CYhfPf73R6SiCiquIiIiIyDnjdlvumbmSpG37mXRNF27q2xxjdD2rN2oZXofrezTl\nw2XbWZ91wOk41Z6Kq4iIiIjIOfL0vPV8vjqTv17cjkviGjkdR07irgtbERTgz5Ofr9PyOA5TcRUR\nEREROQfeXZzGlJ+2cEPPptzUt5nTcaQc6gfW4K4LW/Hzpr18v2G303GqNRVXEREREZGz7Ju1u/jb\nJ2sY2C6cx4a11+nBlcjonk1pHhrIE5+vo9jldjpOtaXiKiIiIiJyFq1Kz+GOGb/QIaouk0Z10Rqt\nlYy/rw8PXdyOLXsOMX3JNqfjVFsqriIiIiIiZ8mO7HxunJpIg8AavDkmgdo1dPfgyujCduH0bhnC\ni99sIie/yOk41ZKKq4iIiIjIWZCbX8y4qcspKnEx7cZuhAcFOB1JTpMxhocviSWvoJh/f7vJ6TjV\n0kmLqzGmsTHme2PMOmPMGmPMXZ7xBsaYr40xmzzv63vGjTFmkjEm1RizyhgTX+a1xni232SMGXP2\nPi0REREREecUlrgY/14i2/flM+WGBFqGBzkdSc5Qu0bBXN2tCe8t3sbmPQedjlPtlGfGtQS4x1rb\nDugBTDDGxAIPAN9aa1sB33oeAwwFWnnexgOTobToAo8B5wHdgceOlF0RERERkarCWst9H69i6dZs\n/nVlHD2ahzgdSSrInwe1JsDfl6e+WOd0lGrnpMXVWptprU32fJwHrAOigMuBaZ7NpgFXeD6+HHjX\nlloC1DPGNAIuAr621mZba/cDXwNDKvSzERERERFx2LNfbWDuip3ce1EbLu8c5XQcqUBhQTWZMKAl\n36zbzYJNe52OU62c0jWuxpgYoAuwFGhorc2E0nILhHs2iwJ2lNkt3TN2vHERERERkSphxrLtvPL9\nZq7p1pjb+7dwOo6cBeN6xxBdvxZPfL4Wl9s6HafaKHdxNcbUAWYBf7LWHjjRpscYsycY/+1xxhtj\nEo0xiXv27ClvPBERERERR/2wYTcPz0mhX+swHr+ig9ZqraIC/H15cGg71mfl8dHyHSffQSpEuYqr\nMcaf0tL6vrV2tmd4l+cUYDzvd3vG04HGZXaPBnaeYPxXrLVTrLUJ1tqEsLCwU/lcREREREQcsWZn\nLhPeT6ZNwyBevS4ef18t3lGVXdwxgm4x9Xn+6w3kFRQ7HadaKM9dhQ3wFrDOWvt8mac+AY7cGXgM\nMLfM+A2euwv3AHI9pxLPBwYbY+p7bso02DMmIiIiIlJp7cw5zI1TlxNcy593xnWjTk2t1VrVGWN4\n5NJY9h4s4pXvNzsdp1ooz5+CegOjgQuMMSs8bxcDTwODjDGbgEGexwBfAFuAVOAN4HYAa2028Diw\n3PP2f54xEREREZFK6UBBMTdOXU5+oYt3xnWjYbDWaq0u4qLrMSI+ircXbGX7vnyn41R5xlrvvaA4\nISHBJiYmOh1DREREROR3il1uxr2znCVb9jF1XHf6tAp1OpKcY1m5BQx49gcGtA3j1eu6Oh2nUjLG\nJFlrE062nU6+FxERERE5RdZaHpy9mgWpe3lqREeV1moqom4At5zfnC9WZ7Fsq04mPZtUXEVERERE\nTtGkb1P5OCmdOy9sxZUJjU++g1RZ4/s1JyI4gMc/W4tby+OcNSquIiIiIiKnYFZSOi98s5ER8VHc\nPbCV03HEYbVr+HHfkDaszshl6qI0p+NUWSquIiIiIiLltCh1L/fPWkWvFiE8PSJOa7UKAFd0jmJg\nu3Ce/GIdS7bsczpOlaTiKiIiIiJSDht35XHL9CSahwUy+fqu1PDTr9JSysfH8PzVnWkaUpsJ7yeT\nkXPY6UhVjv5vExERERE5id0HChj3znJq+fvyzrju1K3l73Qk8TLBAf68cUMCRSVubnkvkYJil9OR\nqhQVVxERERGREzhUWMK4qcvZn1/E22O7EVWvltORxEu1CKvDC1d3JiXjAA/OXo03Lz1a2ai4ioiI\niIgcR4nLzcQPklmflccr18bTIaqu05HEyw2MbcifB7Xmv79k8PbCNKfjVBkqriIiIiIix2Ct5dFP\n1vD9hj08fnkHBrQNdzqSVBITB7RkcGxD/vHFOhal7nU6TpWg4ioiIiIicgyv/biFD5Zu57b+Lbj2\nvCZOx5FK5MjNmpqHBjLhg2R2ZOc7HanSU3EVERGRc+ZgYQnL07JZtHkvuYeLnY4jclyfrNzJP+et\nZ1inSO4d3MbpOFIJ1anpx5QbEihxW8a/l8ThIt2s6Uz4OR1AREREqqa9BwtZs/MAKRm5rN15gDU7\nc0nb9+tZh2ahgXSMqktcdF3iouvRPjKYwJr69USctWxrNn+ZuZLuMQ149so4fHy0VqucnmahgUwa\n1YUbpy7nvlmrmHRNZ639e5r0k6GKSN2dx5ers5i/NovgAH+evbITkbrjnYiInAPWWtL3H2bNzlzW\n7Dzgectl14HCo9tE169F+8hgRsRH0z4yGD9fH1Iyclm5I4fladl8snInAMZAy7A6xEXXIy66Lh2j\n6xLbKJgAf1+nPj2pZjbvOcjN7yYS3aAWU27oSk0//bcnZ2ZAm3D+MrgN/5q/gY5RwYzv18LpSJWS\n8eZbNCckJNjExESnY3glay1rdh5gXkoWX6ZksnnPIQC6NKnHpl0HCfD35fXRXenatL7DSUVEpCop\ncbnZvOdQmZJaOpt6oKAEAB8DLcPr0D6yLu0jg4mNDKZ9o7rUrX3iNS935xV4imwuqzNyWZWew96D\nRQD4+RhaNww6WmTjourRJiKIGn7V44onl9uy60ABGTmHyS9yUeJyU+K2lLgsJW43xS6Ly/P+yHO/\nGnO7KXGVGXN7tnNZit3H2teNy/MaR/Yt8exzzDG3xcfA+a3DGBkfTf824ZX2e7Mnr5ARkxdyuMjF\n7Nt60ySkttORpIqw1jLhg2TmpWQx7cbu9G0V5nQkr2GMSbLWJpx0OxXXysPttvyyYz/zUrKYtyaL\nHdmH8TFwXrMQhnaM4KL2ETQMDmDjrjxumpZIVm4B/xjRkT90jXY6uoiIVEIFxS7WZR44Oou6dmcu\n67PyKCxxA1DTz4e2jYJpH3nkrS5tI4IqZHbUWkvWgQJWpZeW2FXppYU2J7/0utgavj60axR0tMh2\njK5Lq/A6+PlWvsJ0pJim7z9M+v7837w/zM6cw5S4T//3NV8fg9+RN18f/H0Nfj4++Pn+b8zPx+Dv\nW2bM87y/rw++PuZX+/j7+ODra/A/sq+v4VBhCfNSsth7sIj6tf25rFMkI7tG0zGqbqU5LfJwkYtr\n3ljChqwDfDS+J50a13M6klQxhwpLGDl5EZm5BXw6sY/+MOKh4lpFlLjcLNuazbw1Wcxfk8WuA4X4\n+xr6tAxlSIcIBsVG0CCwxu+G3I0cAAAgAElEQVT223+oiNvfT2bxln3c3LcZDwxth6+uzxARkePI\nzS/+1Szqmp0H2LznIEf6UnCA39FZ1PZRpSW1eWjgOS2KR05JXpmew+r0XFal55KSkUteYelsb4C/\nD+0j65a5ZrYuzUPrOH594ukU0/CgmkTXr0V0/dpH30fVr0Wdmr74+vy6aB6rSPr7+BwtrOfq8y92\nufl50x5mJWfw9dpdFJW4aRleh5Hx0VzRJZJGdb33EiaX23Lr9CS+WbeL16/vyuD2EU5Hkipq275D\nXPbyQhrVDWDWbb10TT8qrpVaYYmLRan7+DIlk6/X7mJ/fjEB/j70bx3OkA4RXNAunOCAE59yBaU/\nQJ74bC3TFm/j/NZhTBrVhbq1Tr6fiIhUXdZadh0o/F1JTd9/+Og2DYNr/q+kemZSo+vX8sqZM7fb\nsnXfoaNFdnVGDikZBzhcXHr3zsAavnTwFNmO0fXoFF2XJg1qV+jn4nKXzg6nZ/+vjGbknHoxLX1f\ni8h6tSr9Nb25h4v5fFUms5PTSdy2H2Ogd4tQRnaN4qL2EdSu4V2/rP/tkzVMXZTG34bFMrZ3M6fj\nSBX308Y9jH1nGUM6RPDKtfFe+W/ruaTiWskcLnLx48bdfJmSxXfrdpNXWEJQTT8uaBfO0A4R9Gsd\ndtr/yH+wdDuPzk2hSUht3rwhgeZhdSo4vYiIeCO325K279Cvbpi0ducB9h0qOrpNs9DA0utQPQW1\nfWQwoXVqOpj6zLncltTdB1mVnsPqjFxWpueyLvMARZ5TnIMD/IiLLj29uJOn0EbWDTjuL4/HKqZH\nZ0xz8snMKah2xfRUpO09xOxfMpidnE76/sPUruHL0A6NGNk1ih7NQhyfEX9rwVYe/2wtf+zTjEcu\njXU0i1Qfr/+4mae+XM99Q9pwe/+WTsdxlIprJXCgoJjv1+/my9VZ/LBxNwXFburX9mdQbEOGdmhE\nr5YhFXYnuyVb9nHb9CRcbsvL18bTr7UuCBcRqarS9+fzyvepfLJiJ4c86wb6+xpahQf9bxY1qi7t\nGgVTp5qcplZU4mbjrjzPjZ9Kr5vdkJV3tHCGBNbwXC9bF18fn5MW04bBNX9VRssW1EZ1A6pVMS0v\nt9uSuG0/s5LS+Xx1JgcLS4isG8Dw+ChGxEfTwoE/rM9LyeS295O5KDaCV6+Ld7xES/VhreXOD1fw\n2aqdvD22GwPahDsdyTEqrl4q+1ARX6/NYl5KFgtT91HkchMeVJMhHSIY0j6C7s0anLXrhXZk53Pz\nu4ls3JXHXy+J5cbeMdX+1AQRkaokK7eAV75P5cPl2zEYLu8cSbeYBsRGBtO6YfW5C295FRS7WJ+V\nx+r0HFam57I6PZdNu/NwWxXTs+1wkYuv1+1iVlI6P2/ag9tC58b1GBkfxbBOkdSr/fv7d1S05O37\nGTVlCbGRwcy4uYe+p3LOHS5yMWLyIjL25zN3Yh+ahQY6HckRKq5eZNeBAuavKS2rS7dm43JbouvX\nYmiHCIZ0iKBL4/rn7C98BwtL+PNHK/hq7S6uSojm8Ss6aH0yEZFKbndeAZN/2Mz7S7fjdluu6taY\nCQNaEqX1vE/Z4SIXxqAScw7tPlDA3BU7mZWczvqsPPx9DRe2bciI+KiztrRO2t5DjJi8iKAAP2bf\n1ouQSn56vFReO7LzuezlBYTWqcl/J/SuNmfBlKXi6rAd2flHl61J2rYfgBZhgQzt0IghHSJoHxns\n2Gyn22154ZuNvPRdKglN6zP5+q6EBekfbBGRymbfwUJe/2kL7y5Oo9hlGRkfxR0XtKJxAy2xIJWP\ntZa1mQeYnZzB3BUZ7D1YRIPAGlzWKZIR8VEVtrRO9qEiRk5eRE5+EbNv711tZ7nEeyxM3cvot5Yy\nKLYhk6/rWu1OWVdxdUDq7oPMS8nky5Qs1uw8AED7yGCGtI9gaMcIWoYHOZzw1z5duZN7P15Jg9o1\nmHJDAh2i6jodSUREyiEnv4gpP21h6qI0CopdXNE5ijsubKVfwKXKONbSOq3C6zDiDJfWKSh2cf2b\nS1mVkcuMm8+ja9MGFZxc5PS8+fMWnvh8HfcMas0dF7ZyOs45peJ6DlhrWbPzAPPXZPFlShapuw8C\nEN+knuea1UZev7Dw6vRcxr+XSE5+Mc9d1YmLOzZyOpKIiBxH7uFi3lqwlbcXbOVQUQmXdGzEnwa2\n8ro/jIpUpNz8Yj5f/euldfq0DGVE/KktreN2W+6Y8Qufr87klWvjuSROv/OI97DW8ueZK5mzIoM3\nRicwMLah05HOGRXXs2hDVh6zktOZl5LF9ux8fAyc1yyEoR0jGBwbQUTdAKcjnpLdeQXc+l4Sydtz\nuOvCVtx1Yatqd4qCiIg3O1hYwtSFW5ny0xYOFJQwpH0EfxrUirYRwU5HEzmnfru0TmANX4Z2bMSI\n+JMvrfPUF+t4/actPHRxW8b3a3EOU4uUT0Gxiz+8tohte/OZM7G3I3fadoKKawUrcbn5Zt1upi1K\nY/GWffj7Gnq3DGVohwgGtmtY6S/qLyxx8dDsFGYlpzOkfQTPXdWJwGp4cbiIiDfJLyrh3cXbeP3H\nzezPL2Zgu3D+NLC1Lu2Qas/ttixPy2Z2csbRpXWi6tXiii6Rx1xa573FaTwydw039GzK3y9rr1UV\nxGtl5BzmspcWULe2P3Mm9CY4wN/pSGedimsF2X+oiI8Sd/De4m1k5Bwmql4tru/RlGu6NaZ+4Nm/\nVfu5ZK3lrQVb+ccX62jdMIg3xyQQXd+7T3UWEamKCopdTF+yjdd+3Mzeg0Wc3zqMuwe1pnPjek5H\nE/E6h4tcfLU2i9nJGb9eWqdrNMPiGpGYtp/x7yVyQdtwXh+dgK/OKhMvt2TLPq57cykD2oQxZXRC\nlT8TUsX1DK3deYBpi9KYsyKDwhI3PZuHMKZXDAPbhZ+1dVa9xQ8bdnPHjF+o4evDa6O70i1GNy4Q\nETkXCktcfLhsB698n8ruvEJ6twzh7oGtSdC/wyLlsvtAAXNWZDArKYMNu/Ko4esDBtpGBPHh+B7l\nvh5WxGlTF27lb5+u5a4LW3H3oNZOxzmrVFxPQ4nLzVdrdzF1URrLtmYT4O/D8C7RjOnVtNpdR7R5\nz0FumpZI+v58Hr+8A9d0b+J0JBGRKquoxM1/knbw8nepZOYW0D2mAX8e3JoezUOcjiZSKZVdWmfT\n7oM8e2Uc4UGV6x4kUr1Za7n341V8nJTO66O7clH7CKcjnTUqrqdg38FCPly+g+lLtpGZW0DjBrW4\noUcMVyU0pm7tqn9e+fHk5hczcUYyP2/ay9heMTx8SbsqP9ssInIulbjczE7OYNJ3m0jff5guTepx\nz6A29G4ZomvwRESquYJiF1e/vpjU3QeZM6E3rRpWzTvIq7iWQ0pGLlMXpfHJyp0Ulbjp0zKUMb1i\nuKBtuK5/8ChxuXnqy/W8tWArfVqG8vK1XahXu2pd2ysicq653JZPVmbw7282kbYvn7joutw9qDX9\nW4epsIqIyFGZuYcZ9tICggJKb9ZUt1bVm1RTcT2OYpebeSlZTF2URtK2/dSu4cvI+NLTgbUO3vHN\nXL6Dv85ZTVS9Wrw5JkFfKxGR0+B2Wz5fncmL32xk855DtGsUzJ8HtWZgu3AVVhEROabladmMmrKE\nvq1CeXNMtyo3wVZhxdUY8zZwKbDbWtvBM/Y34GZgj2ezh6y1X3ieexD4I+AC7rTWzveMDwH+DfgC\nb1prnz5ZuIosrnvyCpmxbDvvL93GrgOFNA2pzQ09Y7gyIbpa3Ga6IiSmZXPr9CQKi91MGtWFAW3D\nnY4kIlIpWGuZvyaLF77exIZdebRuWIe7B7bmovYRVf5ukSIicubeW7KNR+akMHFAS/5yURun41So\niiyu/YCDwLu/Ka4HrbXP/mbbWGAG0B2IBL4BjtwGayMwCEgHlgOjrLVrT3TsiiiuK3fkMG1RGp+t\nyqTI5aZf6zDG9mpK/9bh+mXhNGTkHObmaYmsyzrAA0PaMr5fc80SiIgch7WWb9ft5oVvNrJm5wGa\nhwZy18BWXBoXWeX+Yi4iImePtZYHZ6/mw+U7ePW6eC7u2MjpSBWmvMX1pPcEt9b+ZIyJKedxLwc+\ntNYWAluNMamUlliAVGvtFk+4Dz3bnrC4nq6iEjdfpmTyzsI0VuzIoU5NP649rwmjezb93YLUcmqi\n6tXi49t6cu9/VvHUl+vZkJXHP0Z0JMDf1+loIiJew1rLjxv38MLXG1mZnkuTBrV57spOXN45Uje5\nExGRU2aM4e+Xt2fDrjz+8p+VtAirQ5uI6nXp3pksZjXRGHMDkAjcY63dD0QBS8psk+4ZA9jxm/Hz\njvWixpjxwHiAJk1ObQmW3QcKeH/pdj5Ytp09eYU0Dw3kb8NiGdk1miCdDlxhatfw4+Vru9D62yBe\n+GYjW/YeYsroroQH6zbzIlK9WWtZtHkfz3+9kaRt+4mqV4t/juzIiPho/FVYRUTkDNT08+W167ty\n6UsLuPndRD6Z2Lta3TT1dIvrZOBxwHrePwfcCBzrvCcLHOun9THPUbbWTgGmQOmpwicLYq3llx05\nTF2YxpcpmZS4LQPahDOmVwx9W4bqdOCzxBjDXQNb0SaiDnd/tJJhLy/gjRsSiIuu53Q0ERFHLNua\nzXNfbWDp1mwiggN44ooOXJXQmBp+KqwiIlIxGgYH8Nr1XblmymLumPELU8d1rzaXnpxWcbXW7jry\nsTHmDeAzz8N0oHGZTaOBnZ6Pjzd+WgpLXHy2MpNpi9NYlZ5LUE0/RveI4YaeTYkJDTyTl5ZTMKRD\nI5o0COTmdxO58rXFPPOHOC7vHHXyHUVEqojk7ft5/quNLEjdS1hQTf42LJZrujfRJRQiInJWdG1a\nn/+7vAMPzl7NM/PX8+DQdk5HOidOq7gaYxpZazM9D4cDKZ6PPwE+MMY8T+nNmVoByyidiW1ljGkG\nZADXANeezrGzcgt4f+k2Pli6nX2HimgZXofHr+jAiC5RBNY8kzOf5XTFRgYzd2Jvbp+ezF0frmDj\nrjzuGdRGs90iUuW9/N0mnv1qIyGBNfjrxe24vkdTatVQYRURkbNrVPcmpGTk8vqPW+gQWZdhnSKd\njnTWnbTpGWNmAP2BUGNMOvAY0N8Y05nS033TgFsArLVrjDEzKb3pUgkwwVrr8rzORGA+pcvhvG2t\nXVPekNZakrbt551FacxPycJlLRe2bcjYXjH0bhmiu9p6gdA6NZl+03k8OjeFV77fzIasg7x4TWfq\n6I8JIlIFWWt5/uuNvPRdKld0juTJ4R31x1MRETmnHhvWng1Zedz7cenNmmIjg52OdFaddDkcJ3Xt\nmmDvf/2/TFuUxpqdBwgO8OPqbo0Z3SOGJiG1nY4nx2CtZdqiNB7/fB0twgJ584Zu+l6JSJVireXp\nL9fz+k9buDqhMf8Y0bHaXF8kIiLeZXdeAZe9tBA/X8OnE/tQP7Dy3aypwtZxdVLtqNY2fPQLtG5Y\nh7G9mnFFl0hq19BftCuDBZv2MuGDZHwMvHpdV3q2CHE6kojIGbPW8vdP1zJ1URqjezTl75e112UR\nIiLiqBU7crjqtcV0a1afaeO6V7pl16pEcQ1rFmvnfvMTPZvrdODKaOveQ9w0bTnb9uXz2GXtGd2j\nqdORREROm9tt+eucFGYs284f+zTj4Uva6WeTiIh4hZmJO7jv41Xc1KcZD18a63ScU1Le4urVdbxp\nSG16tQjVLwaVVLPQQP47oTd9W4XyyJwU/vrf1RS73E7HEhE5ZS635d6PVzFj2XZu799CpVVERLzK\nVQmNGdOzKW8u2MqcXzKcjnNWeHVxlcovOMCfN8d045bzm/P+0u3c8cEvePMsv4jIbxW73PzpoxXM\nSk7n7oGtufeiNiqtIiLidR6+NJbuzRpw/6xVpGTkOh2nwqm4ylnn62N4cGg7Hhzalnlrspjy0xan\nI4mIlEtRiZs7PviFT1fu5L4hbbhrYCuVVhER8Ur+vj68el08IYE1uOW9JPYdLHQ6UoVScZVzZny/\n5lzcMYJ/zlvP4s37nI4jInJCBcUubpuexLw1WTxyaSy392/pdCQREZETCq1Tk9dHJ7D3YCETPkiu\nUpfpqbjKOWOM4Z8j44gJDeSOGb+w60CB05FERI7pcJGLm99N5Nv1u3n8ig78sU8zpyOJiIiUS8fo\nujw1oiNLtmTz5OfrnI5TYVRc5ZwKCvDnteu7cqiwhAnvV62/AolI1XCosIQbpy5nQepenhkZpzui\ni4hIpTMiPpobezdj6qI0Pk5KdzpOhVBxlXOudcMgnh7ZkcRt+3n6y/VOxxEROSqvoJgxby9j6dZ9\nvHBVZ67q1tjpSCIiIqfloYvb0qtFCA/9dzUrd+Q4HeeM+TkdQKqnyztH8cv2HN5asJUuTepxaVyk\n05FEpJrLzS/mhneWsSYjl5dGxXNJXCOnI4mIiJw2P18fXr42nmEvLeDGqcvpEFUXf1+Dr4/Bz8en\n9L2vwc/H4OvjU+a58j3+374Gf1+fMs+d2uNyfz5n8WslckIPXdyOVek53P/xKtpGBNEyPMjpSCJS\nTWUfKmL0W0vZuCuPV6+LZ3D7CKcjiYiInLEGgTV4c0wCT36+jpzDxZS43LjclhK3xeW2FJ/gcYnL\njduLVrE03rymZkJCgk1MTHQ6hpxFmbmHuXTSAuoH1mDuhN4E1tTfUkTk3NqTV8j1by5l675DvD66\nKwPahDsdSURExCu43RaXPVaptZS4y/nYdaQYu8s8V/q42GUZ3TMmyVqbcLIsagniqEZ1azFpVBdG\nv7WU+2et4qVRXbRGooicM7sOFHDtG0vIyDnMO2O70btlqNORREREvIaPj8EHg78vBPj7npVjjC5v\nlrNydJFT0LtlKPcMbsNnqzKZuijN6TgiUk1k5BzmqtcXk5VbwLRx3VVaRUREvJiKq3iF285vwcB2\nDXny83Ukbct2Oo6IVHE7svO5+vXFZB8q4r2bzuO85iFORxIREZETUHEVr+DjY3juqk5E1qvF7e8n\nsyev0OlIIlJFbdlzkKteX0xeQQkf3NSD+Cb1nY4kIiIiJ6HiKl6jbi1/Jl8fT05+MXfO+IUSl9vp\nSCJSxWzalcfVU5ZQVOJmxs096Bhd1+lIIiIiUg4qruJV2kfW5cnhHVm8ZR/Pfb3R6TgiUoWs3XmA\nq6csAeDD8T2IjQx2OJGIiIiUl4qreJ0/dI1mVPcmTP5hM1+tyXI6johUAavTcxn1xhJq+Prw0fge\ntGqodaNFREQqExVX8UqPDYulY1Rd7pm5krS9h5yOIyKVWPL2/Vz75hLq1PRj5i09aR5Wx+lIIiIi\ncopUXMUrBfj78up18fj6Gm6dnsThIpfTkUSkElq2NZvRby6lQWANZt7akyYhtZ2OJCIiIqdBxVW8\nVuMGtXnx6s5s2JXHX+esxlrrdCQRqUQWpu5lzNvLiKgbwMxbehJVr5bTkUREROQ0qbiKV+vfJpw7\nL2jF7OQMPli23ek4IlJJfL9hN+OmLqdJg9p8OL4nDYMDnI4kIiIiZ0DFVbzeXRe24vzWYfz9k7Ws\n3JHjdBwR8XJfrcnilneTaBlWhxnjexAWVNPpSCIiInKGVFzF6/n4GF68ujNhQTW5/f1k9h8qcjqS\niHipz1dlcvv7ybRrFMSMm3vQILCG05FERESkAqi4SqVQP7AGr14Xz568Qu76aAUut653FZFfm/NL\nBnfMSKZz43pMv+k86tb2dzqSiIiIVBAVV6k0OjWux98ua89PG/cw6dtNTscRES8yc/kO7p65gu7N\nGjDtxu4EBai0ioiIVCUqrlKpjOremJHx0Uz6bhPfb9jtdBwR8QLTl2zjvlmr6NMylHfGdiewpp/T\nkURERKSCqbhKpWKM4YkrOtCmYRB/+nAFO7LznY4kIg56a8FWHp6TwoVtw3njhgRq1fB1OpKIiIic\nBSquUunUquHLa9d3xW0tt7+fTEGxy+lIIuKAyT9s5vHP1jKkfQSTr+9KgL9Kq4iISFWl4iqVUkxo\nIM9d2YnVGbn8/dO1TscRkXPIWsuL32zkn/PWM6xTJC9f24UafvpxJiIiUpWd9Ce9MeZtY8xuY0xK\nmbEGxpivjTGbPO/re8aNMWaSMSbVGLPKGBNfZp8xnu03GWPGnJ1PR6qTwe0juK1/C2Ys285/Enc4\nHUdEzgFrLf+av4EXv9nEyPhoXry6M36+Kq0iIiJVXXl+2k8Fhvxm7AHgW2ttK+Bbz2OAoUArz9t4\nYDKUFl3gMeA8oDvw2JGyK3Im7hnUml4tQnh4TgprduY6HUdEziJrLU98vo5Xf9jMqO6N+dcf4vD1\nMU7HEhERkXPgpMXVWvsTkP2b4cuBaZ6PpwFXlBl/15ZaAtQzxjQCLgK+ttZmW2v3A1/z+zIscsr8\nfH2YNKoL9Wr7c9v0ZHIPFzsdSUTOArfb8ujcNby1YCtje8Xwj+Ed8VFpFRERqTZO9/yqhtbaTADP\n+3DPeBRQ9pzNdM/Y8cZ/xxgz3hiTaIxJ3LNnz2nGk+oktE5NXr0unp05h7ln5grcbut0JBGpQG63\n5aH/rua9JdsY3685jw2LxRiVVhERkeqkoi8MOtZvEvYE478ftHaKtTbBWpsQFhZWoeGk6uratAEP\nX9KOb9btZvKPm52OIyIVxO223D9rFR8u38HEAS15cGhblVYREZFq6HSL6y7PKcB43u/2jKcDjcts\nFw3sPMG4SIUZ0yuGYZ0iee6rDSxM3et0HBE5Q2635YHZq/hPUjp3XtiKewa3VmkVERGppk63uH4C\nHLkz8BhgbpnxGzx3F+4B5HpOJZ4PDDbG1PfclGmwZ0ykwhhjeHpER1qE1eHOGb+QmXvY6Ugicprc\nbsuDs1czMzGdOy9oyd0DW6m0ioiIVGPlWQ5nBrAYaGOMSTfG/BF4GhhkjNkEDPI8BvgC2AKkAm8A\ntwNYa7OBx4Hlnrf/84yJVKjAmn5Mvr4rBcUubn8/maISt9ORROQUHSmtHyXu4I4LWnL3IM20ioiI\nVHfGWu+9kU1CQoJNTEx0OoZUQp+vymTCB8mM7RXD3y5r73QcESmnIzdiOnJNq04PFhERqdqMMUnW\n2oSTbadV26VKuiSuEX/s04ypi9KYuyLD6TgiUg5ut+Wvc0pL64QBLVRaRURE5CgVV6myHhjalm4x\n9Xlg1mo27spzOo6InEBpaU1hxrId3N6/BX8Z3EalVURERI5ScZUqy9/Xh5evjSewph+3vpdEXkGx\n05FE5BjcbsvDc1OYsWw7t/Vvwb0XqbSKiIjIr6m4SpXWMDiAl6/twrbsfO77eBXefE23SHXkdlse\nmZvCB0tLS+t9Kq0iIiJyDCquUuX1aB7CfRe14cuULN5asNXpOCLiYa3l0U9SeH/pdm49X6VVRERE\njk/FVaqF8f2aM6R9BE99uZ5lW7USk4jTrC2daZ2+ZDu3nN+c+4eotIqIiMjxqbhKtWCM4Zkr42jS\noDYTPkhm94ECpyOJVFvWWh6du6a0tPZrzgND2qq0ioiIyAmpuEq1ERzgz+Tr48krKGbiB79Q7HI7\nHUmk2rHW8tgna3hvyTbG92vOA0NVWkVEROTkVFylWmkbEczTI+JYlpbNv+ZvcDqOSLVypLS+u3gb\nN/dtxoMqrSIiIlJOKq5S7VzRJYrRPZoy5actfLk60+k4ItWCtZa/lSmtD13cTqVVREREyk3FVaql\nhy9tR6fG9bj341Vs3nPQ6TgiVZq1lr9/upZpi7dxUx+VVhERETl1Kq5SLdX082XydfH4+xpum55E\nflGJ05FEqqQjpXXqojT+2KcZf71EpVVEREROnYqrVFuR9WoxaVQXNu0+yIOzV2OtdTqSSJVireX/\nPistrTf2bsbDKq0iIiJymlRcpVrr2yqMPw9szdwVO/nTRytI23vI6UgiVYK1lsc/W8c7C9MY1zuG\nRy5VaRUREZHT5+d0ABGnTRjQkvxiF+8s3MpnqzK5onMUd1zQkpjQQKejiVRK1lqe+Hwdby/cyrje\nMTx6aaxKq4iIiJwR482nRyYkJNjExESnY0g1sTuvgNd/3ML0JdsocVuGdyktsE1DVGBFystay5Of\nr+PNBVsZ2yvm/9u79+AqyzuB498nFwKBkIRrYk6SFrS1SBAJIl07LdquIzhdW623trvdnZ3pTtXO\n7szObDv7T7vdtbXdba1dL9VO3XZ2et/WbWcXqqigtduxAipBJJCgCbmQcElCYgi5nGf/OEcEFBRD\nck6S72fGOScvh+T3z5uXr+/zvi9f+qjRKkmSTi+EsDXGuPItP2e4Sifr7B3gu5v38qNnUgF73SUV\nfP7KC6iaW5jp0aSsFmPkq+tf4nu/M1olSdLbY7hKo9R5ZID7n2zkR880M5KMXL+igtuvMGClNxNj\n5GsbdvHgU3uNVkmS9LYZrtI50nFkgPs3N/LjPzaTTEauX5Hg9ivPp3KOASvBydH6mfdX8+U/u8ho\nlSRJb4vhKp1jpwbsJ2oT3HaFAaupLcbInRt28cBTe/mL91fzT0arJEk6C4arNEb29wzw3SdfD9gb\nVia4dY0Bq6knxsidv93FA0/u5c9XV/OVa41WSZJ0dgxXaYzt7xng/s0N/OSP+0jGyA0rK7ntisUk\nSg1YTX4xRr7+23q++2Qjn15dxT9fu9RolSRJZ81wlcZJe89R7t/cyE//uI/IawF7PhUlMzI9mjQm\nYox845F67t/cyKcuS0VrTo7RKkmSzp7hKo2ztu5UwP7s2VTA3riyklsNWE0yMUb+9ZF67jNaJUnS\nOWC4ShnS1n2U+zY38LNn9wFw06WV3LrmfM4zYDXBxRj5t0fruXdTI5+8rIp/MVolSdIoGa5ShrV2\nH+W+TQ38fIsBq4kvxsg3H93NPZsauGVVFXd8zGiVJEmjZ7hKWaK1+yj3bmrgF1v2EQipgL1iMeXF\nBqwmhhgj39q4m39/ooFbVlVyx8dqjFZJknROGK5Slmnp6ufeTY38Yss+ckLg5lWpM7BlxdMzPZp0\nWjFG7tq4m+880cDNl/tMDEwAAAvCSURBVFby1Y8brZIk6dwxXKUste9wP/dtbuAXW1rICYFbVlXy\nOQNWWcholSRJY81wlbLcSQGbE/jkqio+t2YxC2cbsMoO39q4m+88voebVlbyteuMVkmSdO4ZrtIE\nse9wP/duauC/tr4esLeuWcwCA1YZdNfG3dxttEqSpDFmuEoTTPOhdMBuayEvJ/DJy6r43IcMWI2/\nbz+2m28/tocbVya487plRqskSRoz4xKuIYRXgF5gBBiOMa4MIcwBfga8C3gFuDHG2BVCCMDdwDqg\nH/jLGOO2M31/w1VTUfOhfu7ZtIdfbms9HrA3XVrJexcWkdqNpLFz92N7uOux3dxQm+Dr1xutkiRp\nbI1nuK6MMR48Yds3gMMxxjtDCF8ESmOMXwghrAM+TypcLwPujjFedqbvb7hqKms69Cr3PNHAr55r\nZSQZWTR/JuuWlrO2powl5bONWJ0zQyNJdrYd4dfPt/HQ71/mE7UJvmG0SpKkcZDJcK0H1sQY20MI\n5cDmGON7QwgPpN//5NTPne77G64SHOg9xiMv7mfDjnb+0HiIZITquYWsXVrONTXlLK0wYnV2DvYd\nY1tTF1ubu3iuqZsXWro5NpwE4KaVlXz1uhpyjVZJkjQOxitcXwa6gAg8EGN8MITQHWMsOeEzXTHG\n0hDC/wB3xhifTm9/HPhCjHHLKd/zs8BnAaqqqmqbmpre8XzSZHOo7xgbd3bwv3Xt/F/jIUaSkUTp\nDNbVlLN2aRnLK0uMWJ1kJBmp39/L1uYutjV1sa25i6ZD/QDk5wYuOq+Y2upSaqtLWVFV6mOZJEnS\nuHq74Zo3yp9zeYyxLYSwANgYQth1ppneZNsbqjnG+CDwIKTOuI5yPmlSmTurgJtXVXHzqiq6Xh1k\n40sdbKhr5z9+/zIPPrWX84qns7amnHU1ZVxSWepSzymop3+Ibftej9Tnm7t5dXAEgHmzCqitLuFT\nl1WxoqqUpRXFTM/PzfDEkiRJb21U4RpjbEu/doYQHgZWAR0hhPITlgp3pj/eAlSe8NcTQNtofr40\nlZXOnMaNKyu5cWUlPUeHeGxnBxt2tPOff2ji+0+/zMLZBaxdWs66mnJqq0td+jkJJZORxgN9bGvu\nYmtTF9uau2no7AMgNydwYVkR19cmjp9NTZTO8Iy8JEmakN7xUuEQwkwgJ8bYm36/EfgK8GHg0Ak3\nZ5oTY/yHEMI1wO28fnOm78QYV53pZ3iNq3T2egeGeGJXJ+vr2tlcf4Bjw0nmFxVw9UVlrK0pY9W7\n5pCXm5PpMfUO9B0b5oV93WxtSoXqc81dHBkYBqCkMJ8VVaklv5dUlXBxooSZBaNdVCNJkjS2xvwa\n1xDCIuDh9Jd5wI9jjHeEEOYCPweqgGbghhjj4fTjcO4Brib1OJy/OvX61lMZrtLo9B0bZtOuTjbs\naOeJXZ0MDCWZO3MaV11UxjU15axeZMRmqxgjTYf6TzqbWr//CMkIIcAFC2YdP5O6orqURfNmejZV\nkiRNOONyc6axZrhK507/4DCb6w+wvi4Vsf2DI5QW5nPVktSZ2D9ZPI9peUZsphwdHGF7SzfbmruP\nn0099OogAEUFeSyvKjkeqcsrSyiekZ/hiSVJkkbPcJV0WgNDIzy5+wAb6tp57KVO+o4NM3t6Hn+6\npIxrlpVx+fnzKMjzpj1jJcZIW89A6pE06Uh9se0Iw8nU7+N3z5uZjtQSaqtLuWBBkdcoS5KkSclw\nlfS2DAyN8PSeg6zf0c7GnR30DgxTVJDHR5YsZO3SMj74nvneeXaUevqHqGvtYXtrN3UtPTzX3M3+\nIwMATM/P4eJEyfFlv5dUlTB3VkGGJ5YkSRof4/U4HEkT3PT8XD6yZCEfWbKQweEkv288yPrt7Ty6\ns4OHn2tl5rRcPvy+hayrKeND71nAjGlG7Jn0HRtmR2sPdS09bG/toa6lm1fSz00FqJ5byKXvnkNt\nVQm11XO4sLyIfK8zliRJOiPPuEp6U0MjSf7QeIgNO9p55MUODr86yIz8XK68cAFra8q48sIFFE6b\n2v/v6+jgCDvbe9je8nqoNh7o47VfqxUlM6ipKKYmUcyyRDE1FcWUFE7L7NCSJElZxKXCks6Z4ZEk\nz7x8mPV17Tzy4n4O9g0yPT+HyxfPY9H8mSRKC0mUziBRWkhF6QxmTcLHsBwbHqF+fy8vtKTOom5v\n6WFPZx8j6etS5xcVcHGimJqKEpYlillaUcz8Ipf8SpIknYnhKmlMjCQjz75ymA117TzdcJCWrqMc\nG06e9JnSwvwTYnbGhAvboZEkezr6qGvtTodqD7v2H2FoJPX7srQwn2WJkuNnUZclSlg4u8DH0UiS\nJJ0lr3GVNCZycwKrF81l9aK5QOoOuQf7Bmnp6qel62j6v9T73R29PLGrM6vDdiQZ2XugL7Xct7WH\nF1q62dl25PjMRdPzqKko5q8/sOh4qCZKZxipkiRJ48hwlTQqIQTmFxUwv6iAS6pK3/Dn7yRsSwrz\nUyFbckrczkm9vtOwTSYjTYf72d6Survv9pYedrT10D84AkDhtFyWnlfMp1dXsyyROpNaPaeQHB9F\nI0mSlFGGq6QxNZqw3dPZy6b6dxa2MUZauo6mHkPT0kNda+q61N6BYQAK8nJYct5sbqhNUJMo4eJE\nMYvmz/J5qZIkSVnIcJWUUW8nbA+9OnhS0L722nCgj827OxkYemPYBqCrfwiA/NzAhWWz+ejF57Es\nfZff9yz0MTSSJEkTheEqKauFEJg3q4B5swpYXlnyhj8/XdgODUeWJopZVlHMheVFFOT5/FlJkqSJ\nynCVNKG9VdhKkiRp4nOdnCRJkiQpqxmukiRJkqSsZrhKkiRJkrKa4SpJkiRJymqGqyRJkiQpqxmu\nkiRJkqSsZrhKkiRJkrKa4SpJkiRJymohxpjpGU4rhNAL1Gd6DikLzAMOZnoIKcPcDyT3AwncDyab\n6hjj/Lf6UN54TDIK9THGlZkeQsq0EMIW9wVNde4HkvuBBO4HU5VLhSVJkiRJWc1wlSRJkiRltWwP\n1wczPYCUJdwXJPcDCdwPJHA/mJKy+uZMkiRJkiRl+xlXSZIkSdIUZ7hKkiRJkrJa1oZrCOHqEEJ9\nCKEhhPDFTM8jZUII4ZUQQl0I4fkQwpZMzyONhxDCQyGEzhDCjhO2zQkhbAwh7Em/lmZyRmmsnWY/\n+HIIoTV9THg+hLAukzNKYy2EUBlC2BRCeCmE8GII4W/T2z0mTEFZGa4hhFzgXmAtsAS4JYSwJLNT\nSRlzRYxxuc8r0xTyA+DqU7Z9EXg8xngB8Hj6a2ky+wFv3A8A7kofE5bHGNeP80zSeBsG/j7G+D5g\nNXBbugk8JkxBWRmuwCqgIca4N8Y4CPwUuDbDM0mSxkGM8Sng8CmbrwV+mH7/Q+Bj4zqUNM5Osx9I\nU0qMsT3GuC39vhd4CajAY8KUlK3hWgHsO+HrlvQ2aaqJwKMhhK0hhM9mehgpgxbGGNsh9Q8ZYEGG\n55Ey5fYQwvb0UmKXR2rKCCG8C7gEeAaPCVNStoZreJNtPrdHU9HlMcYVpJbN3xZC+GCmB5IkZcz9\nwGJgOdAOfDOz40jjI4QwC/gl8HcxxiOZnkeZka3h2gJUnvB1AmjL0CxSxsQY29KvncDDpJbRS1NR\nRwihHCD92pnheaRxF2PsiDGOxBiTwPfwmKApIISQTypafxRj/FV6s8eEKShbw/VZ4IIQwrtDCNOA\nm4HfZHgmaVyFEGaGEIpeew9cBew489+SJq3fAJ9Jv/8M8OsMziJlxGv/UE/7OB4TNMmFEALwfeCl\nGOO3TvgjjwlTUIgxO1fgpm/x/m0gF3goxnhHhkeSxlUIYRGps6wAecCP3Q80FYQQfgKsAeYBHcCX\ngP8Gfg5UAc3ADTFGb1yjSes0+8EaUsuEI/AK8DevXecnTUYhhA8AvwPqgGR68z+Sus7VY8IUk7Xh\nKkmSJEkSZO9SYUmSJEmSAMNVkiRJkpTlDFdJkiRJUlYzXCVJkiRJWc1wlSRJkiRlNcNVkiRJkpTV\nDFdJkiRJUlb7fwGaiJIhTr0CAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24d0c640048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#一天内发推特的时间段\n",
    "%matplotlib inline\n",
    "time = pd.Series(index=data.created_at)\n",
    "hours = list({i.hour for i in time.index})\n",
    "counts = {}\n",
    "for i in hours:\n",
    "    c = 0\n",
    "    for t in time.index.hour:\n",
    "        if i == t:\n",
    "            c += 1\n",
    "    counts[i]=c\n",
    "    \n",
    "pd.Series(counts).plot(figsize=(16,4), label=\"tweets_count\", legend=True, title='Tweets per hour');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source</th>\n",
       "      <th>source_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Twitter Web Client</td>\n",
       "      <td>12178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Twitter for Android</td>\n",
       "      <td>14545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>5316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>otther</td>\n",
       "      <td>1625</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                source  source_count\n",
       "0   Twitter Web Client         12178\n",
       "1  Twitter for Android         14545\n",
       "2   Twitter for iPhone          5316\n",
       "3               otther          1625"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#发推特的设备分析\n",
    "tweets_source = data[['source']]\n",
    "tweets_source['source_count'] = 1\n",
    "tweets_source = tweets_source.groupby('source').agg('count').reset_index()\n",
    "tweets_source.source[tweets_source.source_count<500]='otther'\n",
    "tweets_source = tweets_source.groupby('source').agg('sum').reset_index()\n",
    "tweets_source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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w6J7xUUlTB7sTXupd4PyyOq/okX1FxRceDPKLrwMyMlNGell2LJmvz8uTxO4f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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24d0c65d390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "labels=tweets_source.source.values\n",
    "sizes=tweets_source.source_count.values\n",
    "colors=['lightgray','lightcoral','yellowgreen','lightskyblue']\n",
    "explode=0,0.1,0,0\n",
    "\n",
    "plt.pie(sizes,explode=explode,labels=labels,colors=colors,autopct='%1.1f%%',shadow=True,startangle=180)\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24d0b18da58>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2FykZNn8T4HuZuWuPtZgzQ3Iq1dKuP/Kjtp5cRHPV701naE6Z57lSLeZ0k1Nw\nPMy6cTXInLGUPMWXZqeN1jk/0S7rMqdSLeaM7yU0n8E18n2AAazoMGOQOdWe49mYU6mWijnVxsQg\ncp6gubLxXSPm79Au65U5MyenUi3QfEbxK3j6lbAD+MYMzqn0PFeqxZxucqqNh9k4rgaZM6qqDerp\nwPUR8W/85yWhd6b5kPq/7DinUi3mjO9q4JHM/MrIBe3RpK4yBplT7TmejTmVaqmYU21MDCLnj4Av\nRcStPPW5eQ5wYh+1mDNzcirVAs2V1Rdl5rdGLoiIK2dwTqXnuVIt5nSTU208zMZxNcicUZU8xRee\nPAXtFTRvvA1giObCHv185t5AcirVYs7GqdpzPBtzKtVSMWc2iuaz6Vbw1Ofmuuz/qpPmzJCcSrXM\nZpWe50q1mNNdzmxU7Tme0n2Vk/ycmq4m4PAqOZVqMcd9bo773JyB7fOeP2PWnNmRU6kWc9zn5rjP\nzWmzBhU01RNwfZWcSrWY4z43x31ujvvcnJlfiznuc3Pc5+Y0U8mPmRlDPxf0mOqcSrWY001OpVrM\n6SanUi3mdJNTqRZzusmpVIs53eRUqsWcbnIq1WJOL0Ftx1teRKzIzGsr5FSqxZxucirVYk43OZVq\nMaebnIhYmplDA6jFnBmSU6kWc7rJqVSLOd3kVKrFnN6UPYIaESsiYt/29m7Ab0TEq6Yjp1It5nST\nU6mWMUz6CmnmdJJhzgzJiYjfAN4QES83Z+PIqVTLbMqJiP0iYov29mYRcRrwkYh4f0Rs2WVOpVrM\n6SanUi0DznlnROw0fN5EmsFqOWPmVzyCGhGnAq+k+RicLwD7AVcCL6O5+uTpXeVUqsWcbnIq1dLm\nXDZyFnAwcAVAZr7GnMnlVKrFnG5yIuLazFzR3v4vwNuBS4CXA/+UmWf0WIs5MySnUi2zPOd7wJ6Z\nuS4izgYeAS4GDm3nv7arnEq1mNNNTqVaBpzzEPAw8O/ABcBFmbmml20r54wpB/Rm1kFOwI3AHGAB\n8FNgi3b+ZsB3usypVIs5G+0+vx74B+Ag4KXt13vb2y81Z/I5lWoxp7N9fsOw29cBS9rbC4Eb+6jF\nnBmSU6mWWZ6zetjt60cs+1aXOZVqMcd9PsmcG2jOfH05cC6wBvhX4Fhg85maM9ZU9RTfdZn5eGY+\nAvx7Zv4UIDN/ATzRcU6lWszpJqdSLQDLgVXAe4CHMvNK4BeZ+ZXM/Io5A8mpVIs53eQ8IyK2jojF\nNGcTrQHIzIeBdX3UYs7MyalUy2zO+W5EvKW9/e2IWA4QEc8FHus4p1It5nSTU6mWQeZkZj6Rmf+W\nmccDzwT+FjgMuH0G54yZXm5wAF3NAAAEiklEQVQCrgEWtLefMWz+lvRxCeNB5FSqxZyNc58P224p\ncBHwN8Dd/W5vzsyqxZypzQHupPkjekf7dft2/iL6e1XbnBmSU6mWWZ6zJfB3NKf+XUPzT/jtwFdo\nTmnsLKdSLea4zyeZc8MGlm02U3PGmqq+B3XTzPyPUeZvC+yQmTd2lVOpFnO6yalUyxi5rwYOyMw/\nm8j25sysWszpLqfNWgBsl5l3mLNx5FSqZTblRMTmwLNprsMwlJn3TfD7TzqnUi3mdJNTqZZB5ETE\nczPz+xP53pVzxsyv2KBuSEQsysyfV8ipVIs53eRUqsWcbnIq1WJONzmVajGnm5xKtZjTTU6lWszp\nJqdSLeZsWNX3oG7ITYVyKtViTjc5lWoxp5ucSrWY001OpVrM6SanUi3mdJNTqRZzusmpVIs5GzB3\nEFUMWkS8e6xFNO+F6CynUi3mdJNTqRZzusmpVIs53eRUqsWcbnIq1WJONzmVajGnm5xKtZgzcVWP\noL4P2BrYfMS0iP5qHkROpVrM6SanUi3mdJNTqRZzusmpVIs53eRUqsWcbnIq1WJONzmVajFnoiZz\nhaWpmoBvAPuMseyeLnMq1WKO+9wc97k57nNz3OfmuM/NqV+LOROfJrXxVE3A82g/IHqUZdt1mVOp\nFnPc5+a4z81xn5vjPjfHfW5O/VrMmfg0467iK0mSJEmanUq+BzUitoyIMyLi5ohY206r23lbdZlT\nqRZzusmpVIs53eRUqsWcbnIq1WJONzmVajGnm5xKtZjTTU6lWsyZuJINKvAp4AHgoMxcnJmLgYPb\neRd1nFOpFnO6yalUiznd5FSqxZxucirVYk43OZVqMaebnEq1mNNNTqVazJmoyZ4jPBUTcMtElk1F\nTqVazHGfm+M+N8d9bo773Bz3uTn1azFn4lPVI6h3RcSfRMR262dExHYRcRJwT8c5lWoxp5ucSrWY\n001OpVrM6SanUi3mdJNTqRZzusmpVIs53eRUqsWcCaraoL4RWAx8JSIeiIifAFcC2wBv6DinUi3m\ndJNTqRZzusmpVIs53eRUqsWcbnIq1WJONzmVajGnm5xKtZgzUZM9BDtVE/BrwMuARSPmH9Z1TqVa\nzHGfm+M+N8d9bo773JyZV4s57nNzesyebMBUTMA7gVuAzwJ3AkcMW3Z9lzmVajHHfW6O+9wc97k5\n7nNz3Ofm1K/FnIlPk9p4qibgRtpuHFgGrATe1d6/ocucSrWY4z43x31ujvvcHPe5Oe5zc+rXYs7E\np7nUNCczfw6QmXdGxEHAxRHxLCA6zqlUiznd5FSqxZxucirVYk43OZVqMaebnEq1mNNNTqVazOkm\np1It5kxQ1Ysk/Sgifn39nfYJOBzYFtij45xKtZjTTU6lWszpJqdSLeZ0k1OpFnO6yalUiznd5FSq\nxZxucirVYs5E5SQPwU7FBCwFth9j2QFd5lSqxRz3uTnuc3Pc5+a4z81xn5tTvxZzJj5FGyRJkiRJ\n0rSqeoqvJEmSJGkjY4MqSZIkSSrBBlWSJEmSVIINqiRJkiSpBBtUSZIkSVIJ/x/aMtzwSvxCJgAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24d0b166240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_ad = data[data.source == 'Twitter for Android']\n",
    "df_ip = data[data.source == 'Twitter for iPhone']\n",
    "df_other = data[(data.source != 'Twitter for Android') & (data.source != 'Twitter for iPhone')]\n",
    "def get_tweets_by_source(df_source):\n",
    "    df_source.index = df_source.created_at\n",
    "    result = {}\n",
    "    for t in df_source.created_at:\n",
    "        time = str(t)[:7]\n",
    "        result[time] = len(df_source[time])\n",
    "\n",
    "    return result\n",
    "\n",
    "ad_tweets = get_tweets_by_source(df_ad)\n",
    "ip_tweets = get_tweets_by_source(df_ip)\n",
    "other_tweets = get_tweets_by_source(df_other)\n",
    "\n",
    "ad = pd.Series(data=ad_tweets)\n",
    "ip = pd.Series(data=ip_tweets)\n",
    "other = pd.Series(data=other_tweets)\n",
    "\n",
    "ad.plot(figsize=(16,4), label=\"android\", legend=True,kind='bar',color='green')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24d0b1819e8>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JKoITVEmSJElSEfwcVElSz/CzEiVJmtzcgypJkiRJKoITVEmSJElSEZygSpIkSZKK4ARV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\ngipJkiRJKsL/B7BsoUsbP2yLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24d0b181a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ip.plot(figsize=(16,4), label=\"iphone\", legend=True,kind='bar',color='grey')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24d0b7f4e80>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7yHXcN+ADVFe4PQH4F+V2Qln2Z6OWT1Eb/wgcusA2um1QebkfaR3G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\n7Mxk7BQyFJ0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24d0b50a5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "other.plot(figsize=(16,4), label=\"other\", legend=True,kind='bar',color='pink')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
